AI Prompt Engineer / Agentic AI Engineer

About the roles

Four direct-hire AI engineering positions with the same hiring employer. All roles share the same locations, work model, travel expectations, and compensation framework.

Locations & work model

• Locations: New York, Bay Area, Dallas, or Chicago
• Work model: Hybrid — no fully remote option
• Travel: Approximately 25% when necessary
• Office attendance: Exact weekly onsite schedule remains pending

Compensation & benefits

• Annual base salary: USD 150,000–200,000, with potential flexibility up to USD 220,000 for exceptional candidates (subject to approval)
• Benefits: Medical, dental, and vision coverage; disability and life insurance; 401(k) with company match; paid leave; parental leave
• Bonus: Performance-based bonus indicated; individual terms to be confirmed

Work authorization

• US citizens and Green Card holders preferred
• H1B transfers possible
• OPT, STEM OPT, and EAD candidates may be considered if they have completed a master's degree and started working in the US (subject to individual confirmation)
• For H4-EAD or other authorization: provide category, expiration date, and sponsorship/transfer requirements
• No minimum two-year EAD validity requirement confirmed
• Candidates must join the hiring employer directly (not BestInfos W-2 payroll)

JD1: Forward Deployed Engineer — Agentic AI

Combines senior client engagement with hands-on engineering, translating business challenges into working AI solutions and taking them from rapid proofs of value toward MVP and production delivery.

Required background

• 8+ years in full-stack engineering, solution architecture, or technical consulting with significant client-facing delivery
• Strong Python plus TypeScript, Java, or Go
• Practical experience with LLMs, agent orchestration, tool calling, planning/execution loops, and memory patterns
• RAG, embeddings, chunking, vector databases, and retrieval evaluation
• APIs, data pipelines, enterprise integrations, and sound software architecture
• Cloud-native engineering on AWS, Azure, or GCP (containers, CI/CD, observability)
• Ability to explain technical decisions and measurable business value to senior stakeholders

Preferred qualifications

• Production GenAI experience
• Integrations with platforms such as ServiceNow, Salesforce, SAP, Microsoft, Databricks, or Snowflake
• Demonstrated ability to personally build solutions, develop evaluation methods, and address security, access controls, human oversight, reliability, latency, and cost

JD2: AI Prompt Engineer / Agentic AI Engineer

Hands-on engineering role focused on developing agents that reason, use tools, and execute enterprise workflows. No minimum years specified — assess demonstrated engineering depth.

Key requirements

• Experience building LLM applications and agent workflows using Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or comparable frameworks
• Hands-on MCP servers, tools, API orchestration, and enterprise connectivity
• Python, TypeScript, or similar programming languages
• Prompt optimization, agent planning, memory, context management, and multi-step execution
• RAG, embeddings, vector databases, and knowledge grounding
• Familiarity with Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable platforms
• Agent evaluation, testing, deployment, monitoring, troubleshooting, security, and governance

Preferred qualifications

• Enterprise copilots, AI assistants, and healthcare or regulated-system integrations

JD3: AI Lead Engineering — Enterprise AI, Cloud & Platform Transformation

Combines AI engineering with enterprise platform design, cloud transformation, and production operations.

Required experience

• 12+ years across AI, DevOps, cloud engineering, SRE, or platform engineering
• 3+ years hands-on AI-stack experience
• 5+ years designing enterprise platforms
• 3+ years implementing AIOps or observability platforms (must be demonstrated)
• Enterprise cloud transformation, production AI/ML environments, and mission-critical or regulated platforms
• Strong coordination with architecture, operations, security, and delivery teams
• Python (mandatory)

Relevant technologies

• GenAI, LLMs, RAG, AgentCore, MCP, AWS Bedrock, SageMaker, vector databases, model lifecycle management
• AWS, Azure, GCP
• Engineering copilots (e.g., Kiro, GitHub Copilot)
• Infrastructure automation, CI/CD, Kubernetes, Docker, service meshes
• Terraform, Datadog, Dynatrace, Splunk, Prometheus, OpenTelemetry

Specific tools are listed as preferred in several areas; not every named product is required.

JD4: AI Architect / FDE Healthcare

Focuses on AI-enabled enterprise architecture, GCP engineering, and integration in a healthcare environment. GCP/Vertex AI and Java/Spring Boot are central requirements.

Required background

• 12+ years overall IT experience with substantial cloud, enterprise, integration, or AI/ML architecture experience
• Strong hands-on GCP and cloud-native architecture
• Vertex AI, GenAI solution design, prompt engineering, model integration, governance, and production deployment considerations
• Strong Java and Spring Boot (microservices, REST APIs, security, scalable backend design)
• Enterprise integration connecting modern and legacy platforms
• Ability to evaluate and apply AI productivity tools such as Claude and Antigravity
• Strong consulting and communication skills with senior business and technology stakeholders

Preferred qualifications

• Healthcare, clinical operations, payer/provider integration, regulated environments
• Relevant Google Cloud certifications

Assessment & interview process

• 45-minute CoderPad assessment covering cloud expertise
• Technical panel and client interviews
• HR discussions
• Sequence follows per-candidate instructions; CoderPad does not necessarily precede L1 for candidates already in process
• Candidates can familiarize themselves with the platform at coderpad.io (general website, not assessment link)
• At assessment stage: coordinate availability beforehand; test must be completed within 24 hours of receiving the individual link

Submission requirements (per qualified & interested candidate)

• Updated resume/profile in Word format
• Completed summary table (provided separately)
• Brief role-fit note identifying proposed role and strongest evidence of relevant engineering experience
• Confirmed interest and interview availability, including time zone
• Contact details, current employment status/title/company, work authorization and sponsorship needs, travel acceptance
• Role-specific skills needed to establish fit
• If existing profile does not clearly demonstrate personal contribution: brief technical example (2–3 sentences covering solution, technologies, production status, and results)
• For JD3: capture required AI, platform-design, and AIOps/observability experience separately